How to Generate a PRD for Claude Code and Cursor

AI coding tools like Claude Code and Cursor thrive on clear, structured input. To get the best results, developers need to create detailed, machine-readable Product Requirements Documents (PRDs). These documents help the AI understand project goals, user needs, and technical details without ambiguity, enabling smarter suggestions and better code.

Key Takeaways:

AI-ready PRDs differ from traditional PRDs by using structured, explicit formats that tools can process.
They include five key sections: Vision and Goals, User Personas and Use Cases, Success Metrics and KPIs, Feature Requirements, and Acceptance Criteria and Edge Cases.
Tools like CodeRide's PRD Generator simplify the process by turning your project brief into a structured PRD compatible with Claude Code and Cursor.

Why It Matters:

AI tools rely on precise input to deliver consistent, accurate results. A well-structured PRD minimizes errors, reduces back-and-forth, and ensures AI tools align with your project vision. Whether you're coding today or revisiting a project later, an updated PRD keeps everything on track.

Want to streamline your AI-driven development? Start with a quality PRD.

How PRD-First Coding with AI Changed My Workflow

What Makes an AI-Ready PRD Different

An AI-ready Product Requirements Document (PRD) stands out because it’s designed to be directly interpreted by AI tools. Unlike traditional PRDs, which rely on human interpretation, AI-ready PRDs use a structured format that tools like Claude Code and Cursor can process without ambiguity.

The key difference lies in how requirements are presented. Instead of vague descriptions, an AI-ready PRD organizes information into clear, machine-readable sections. This ensures that AI tools can parse the data accurately and apply it effectively, leaving no room for misinterpretation.

Core Parts of an AI-Ready PRD

An AI-ready PRD includes five critical sections that work together to provide AI tools with comprehensive project context. Each section addresses the "what", "why", and "how" of the project.

Vision and Goals: This section sets measurable objectives. For instance, instead of saying "improve user experience", an AI-ready PRD would specify, "reduce onboarding time from 10 to 3 minutes."
User Personas and Use Cases: Here, the document defines the target users and their needs in detail. It goes beyond basic demographics, describing behaviors, challenges, and scenarios. For example, instead of simply stating "busy professionals", it might specify "marketing managers who need to create campaign reports in under 15 minutes while juggling multiple data sources."
Success Metrics and KPIs: This section outlines specific metrics to measure success. These could include both technical metrics (e.g., page load times under 2 seconds) and business metrics (e.g., higher conversion rates or improved engagement).
Feature Requirements: Features are broken down into actionable components, complete with user stories, technical constraints, and integration details. This section also specifies edge cases and error-handling requirements, ensuring nothing is left to guesswork.
Acceptance Criteria and Edge Cases: This section defines the conditions for feature completion, including test scenarios, error conditions, and boundary cases. These details help AI tools understand the full scope of implementation.

Together, these sections highlight the structured nature of AI-ready PRDs, making them fundamentally different from traditional PRDs.

Standard PRDs vs AI-Ready PRDs

The differences between standard and AI-ready PRDs become clear when comparing their formats and levels of detail. Here’s how they stack up:

Aspect	Standard PRD	AI-Ready PRD
Format	Narrative text	Structured, detailed sections
Requirements Detail	General feature descriptions with assumed context	Explicit requirements, including edge cases and error handling
Success Criteria	Broad goals like "improved user satisfaction"	Specific metrics with defined targets and measurement methods
Technical Specifications	Basic functional requirements	Detailed constraints, integration points, and performance benchmarks
Context Preservation	Relies on team knowledge	Self-contained with all necessary context

One of the biggest distinctions lies in context preservation. Traditional PRDs often depend on shared team knowledge - insights gained from discussions, past projects, or assumptions. AI tools, however, lack access to this background information. That’s why AI-ready PRDs are designed as self-contained documents, including all the context needed for AI tools to function effectively.

Formatting and schema compliance are also crucial. AI-ready PRDs adhere to the Model Context Protocol (MCP), ensuring compatibility with tools like Claude Code and Cursor. This standardized structure allows AI tools to quickly locate relevant information, maintain context across sessions, and provide accurate, context-aware suggestions.

Step-by-Step: Generate a PRD for Claude Code and Cursor with CodeRide

Claude Code

Creating a PRD (Product Requirements Document) with CodeRide makes it easy to turn your project idea into a structured, AI-ready document for tools like Claude Code and Cursor in just a few minutes.

How to Use the CodeRide PRD Generator

Start by visiting the PRD Generator on the CodeRide platform and entering your project concept.

The tool is designed to work with various input methods to suit different workflows. You can type your project brief directly into the generator. For instance, if you're working on a task management app, you might input something like: "Develop a productivity app for remote teams that integrates with Slack and tracks project milestones with automated reporting."

Alternatively, you can upload research files such as user interviews, market analysis, or feature specifications. The generator supports multiple file formats, including PDFs, Word documents, and text files. It extracts the key details from these materials to populate your PRD.

Once your input is processed, the generator automatically structures your PRD into five key sections: Vision and Goals, User Personas and Use Cases, Success Metrics and KPIs, Feature Requirements, and Acceptance Criteria and Edge Cases. Each section translates your ideas into actionable details designed for seamless AI integration. This ensures every part of the PRD contributes to improving AI-driven development.

After the draft PRD is generated, review each section carefully. For example:

The Vision and Goals section outlines measurable objectives based on your input.
User Personas highlight behaviors and challenges of your target audience.
Success Metrics include specific, quantifiable targets.
Feature Requirements break down functionality into detailed components with technical specs.

You can edit these sections to refine the document further. Add technical constraints, tweak user scenarios, or include additional edge cases to ensure the PRD aligns perfectly with your project’s needs.

Once you're satisfied with the PRD, it’s ready for export and integration.

Export and Import the PRD into Claude Code or Cursor

After finalizing the PRD, download it as a Markdown file. The file is formatted to work seamlessly with both Claude Code and Cursor, ensuring smooth integration.

In Claude Code, you can import the PRD into your project via Projects memory. This feature treats your PRD as a persistent reference document. Whenever you start a new coding task, ask questions, or generate code, Claude Code uses the PRD as a guide. This eliminates the need to repeatedly explain your project’s objectives or features.

For Cursor, the process is similar. Import the PRD into your project workspace through the Context Files system. Once uploaded, the PRD becomes a permanent reference for all AI-assisted coding activities, such as code completion, debugging, or feature development. The AI assistant can pull specific details - like user personas or success metrics - directly from the PRD to ensure consistency throughout the development process.

Both platforms make the PRD’s sections searchable within their AI systems. This means you can reference specific parts, like acceptance criteria or technical requirements, simply by mentioning them in your prompts.

MCP Schema Alignment for Persistent Context

Every PRD generated with CodeRide adheres to the MCP schema, ensuring consistency and compatibility across tools like Claude Code and Cursor.

The MCP schema ensures that your PRD retains its structure and terminology no matter where it’s used. For example:

The Vision and Goals section always follows a standard format.
User Personas and Feature Requirements are consistently organized.

This uniformity is especially useful when switching between platforms or collaborating with team members who use different tools. A PRD created for Claude Code works just as well in Cursor, and vice versa.

The MCP-compliant structure also allows your PRD to serve as a long-term reference for your AI tools. Whether you’re adding a new feature today or revisiting the project weeks later, the PRD ensures that the AI assistant understands your goals, user needs, and technical details without requiring re-explanations.

For instance, if you’re working on user authentication today and data visualization next week, both tasks will rely on the same foundational PRD. This keeps your project consistent and aligned with your overall vision, no matter where you are in the development cycle.

Tips for Better AI Performance with Quality PRDs

A well-crafted, detailed PRD (Product Requirements Document) can significantly improve how tools like Claude Code and Cursor perform, ensuring they deliver accurate and effective results.

Add Edge Cases and Acceptance Criteria

To get the most out of AI tools, it's crucial to include edge cases and acceptance criteria in your PRD. These details help clarify how the system should handle complex scenarios, leaving no room for ambiguity.

For instance, instead of vaguely stating, "users can upload files", you could specify: "Users can upload files up to 10MB in size, supporting .pdf, .docx, and .txt formats. A progress bar should display during the upload, and an error message should appear if the file exceeds the size limit or uses an unsupported format." By defining file size limits, supported formats, and user feedback mechanisms, you make it easier for the AI to understand the behavior you expect.

Similarly, avoid general statements like "the login system should be secure." Instead, provide specifics: "Users must enter a valid email and password. Accounts should lock after three failed attempts, and sessions should expire after 30 minutes of inactivity." This level of detail ensures the AI generates code that meets your exact requirements, minimizing the need for follow-up clarifications.

Tools like the Feature Requirements section in CodeRide's PRD Generator can help you include these specifics. When reviewing your PRD, look for opportunities to add measurable success criteria, error conditions, and detailed user scenarios. The more precise your PRD, the more equipped your AI assistant will be to create reliable, functional code right from the start.

Keep PRDs Updated Throughout Development

Your PRD isn't a one-and-done document - it should evolve alongside your project. As development progresses, new requirements, user feedback, or technical constraints might emerge, and keeping your PRD updated ensures that Claude Code and Cursor always work with the most current context.

For example, if user testing reveals that your navigation design isn’t mobile-friendly, update the PRD to reflect the revised approach. This helps your AI tools stay aligned with the latest project vision rather than relying on outdated assumptions.

Make it a habit to review and update your PRD regularly - weekly during active development or after major milestones. Re-importing the updated PRD ensures that your AI assistant stays synced with the latest requirements. This practice not only streamlines development but also reduces the risk of miscommunication or errors later on.

Once updated, consider breaking your PRD into smaller, focused segments to make it even more effective.

Connect Features to Context Files

Organizing your PRD into feature-specific context files can significantly enhance the efficiency of AI tools like Claude Code and Cursor. Instead of treating your PRD as one massive document, divide it into targeted sections that correspond to specific project areas.

For example, create a context file for user authentication that includes relevant PRD details, API documentation, and security protocols. Another context file could focus on the dashboard interface, containing UI specifications, wireframes, and interaction flows. This modular approach allows the AI to focus on the exact information it needs for a given task, rather than sifting through unrelated content.

Both Claude Code's Projects memory and Cursor's Context Files support this method, letting you activate the most relevant context files based on the task at hand. At the same time, maintain a master PRD file to provide a high-level overview of the project while using these smaller files for detailed guidance.

With tools like CodeRide's full project context feature, you can seamlessly organize your PRD into logical segments that integrate smoothly with your AI coding platform. This setup ensures that your AI tools deliver precise, task-oriented assistance throughout the development process.

Conclusion: Create AI-Ready PRDs with CodeRide

A well-crafted PRD is the backbone of leveraging AI coding IDEs effectively. Tools like Claude Code and Cursor have reshaped the way developers approach their workflows, but their success hinges on the quality of the input they receive. Simply put, the better the context, the better the results. That’s why a structured, machine-readable PRD isn't just a nice-to-have - it's a necessity for achieving consistent and accurate outcomes with these AI tools.

Throwing random notes into the mix leads to inconsistent outputs. On the other hand, a detailed PRD - with clear acceptance criteria, edge cases, and success metrics - minimizes back-and-forth clarifications and speeds up feature development.

This is where CodeRide's PRD Generator steps in. It takes your product brief and organizes it into structured sections that AI tools can easily interpret. With the MCP schema, integration across AI platforms becomes effortless.

Investing the time to create a solid PRD pays dividends throughout the development process. Your AI assistant can produce accurate results with fewer iterations, saving time and energy.

FAQs

What makes an AI-ready PRD better than a traditional PRD for software development?

An AI-ready PRD is tailored to integrate effortlessly with AI tools like Claude Code and Cursor, ensuring more precise and consistent outcomes. Unlike traditional PRDs, which are crafted mainly for human stakeholders, these are formatted specifically for AI systems to easily process and understand. They accommodate various content types, such as text, images, and videos, making prompts and context clear and actionable.

With an AI-ready PRD, developers can improve collaboration between AI systems and human teams, minimize mistakes, and streamline workflows. This structured method allows AI tools to better grasp project requirements, resulting in quicker and more dependable development progress.

How does the CodeRide PRD Generator work seamlessly with AI tools like Claude Code and Cursor?

The CodeRide PRD Generator is designed to work effortlessly with AI tools such as Claude Code and Cursor by adhering to a standardized context schema built on the MCP (Model Context Protocol). This structured approach ensures that these AI-powered IDEs can easily process and make use of the PRDs.

By producing machine-readable PRDs, CodeRide enhances compatibility with features like Claude Code’s project memory and Cursor’s context files, keeping your workflows streamlined and optimized for AI integration.

Why is it essential to keep your PRD updated during development, especially for AI-driven projects?

Keeping your PRD (Product Requirements Document) current is a must for AI-driven projects. Why? Because tools like Claude Code or Cursor depend on precise and up-to-date information to function effectively. AI thrives on structured inputs, and outdated details can lead to errors or inconsistent outcomes.

When your PRD is regularly updated, it helps align AI outputs with your project’s shifting goals, minimizes mistakes, and streamlines the development process. This way, your AI tools can continue to perform reliably and deliver results that match your expectations.